Elektric-Elektronic Engineering

Galtung (1985) argues that just one global and holistic conceptualization of peace is not possible because, like humanity, “the concept of peace is fragmented” (p. 155). A quick review of the literature on peace studies, enabled by the joint efforts of social sciences and peace activism, shows that a unique definition of peace is still not possible (Christie, Tint, Wagner & Winter, 2008; for a detailed review see, Büyükakıncı, 2018). Therefore, it is an important scientific challenge to evaluate the contents and functions of different conceptualizations of peace in various societies. We chose the Social Representations Theory developed by Moscovici (1988) as the theoretical framework of this study. Social representations contain a system of values, ideas, and practices that serve to make sense of the social order by communication through shared codes of the social-historical background of the society as well as the individuals (Sammut & Howarth, 2014). Social representations operate...

The electric power industry sector has become increasingly aware of how counterproductive voltage sag affects distribution network systems (DNS). The voltage sag backfires disastrously at the demand load side and affects equipment in DNS. To settle the voltage sag issue, this paper achieved its primary purpose to mitigate the voltage sag based on integrating a hydrogen fuel cell (HFC) with the DNS using a distribution static synchronous compensator (D-STATCOM) system. Besides, this paper discusses the challenges and opportunities of D-STATCOM in DNS. In this paper, using HFC is well-designed, modeled, and simulated to mitigate the voltage sag in DNS with a positive impact on the environment and an immediate response to the issue of the injection of voltage. Furthermore, this modeling and controller are particularly suitable in terms of cost-effectiveness as well as reliability based on the adaptive network fuzzy inference system (ANFIS), fuzzy logic system (FLC), and proportional–in...

Dynamic Voltage Restorer (DVR) is used in power distribution system to protect sensitive load in voltage disturbances. Voltage sag is one of the most important power quality problems challenging the utility industry. Voltage sags can be compensated by voltage and power injection into the distribution system. DVR is developed using Mamdani-type fuzzy inference system and Sugeno-type fuzzy inference system. They are two input and one output. Both Mamdani-type fuzzy inference system and Sugeno- type fuzzy inference system are simulated using MATLAB fuzzy logic toolbox. This paper outlines the basic difference between these two fuzzy inference system and their simulated results were compared.

Stability control system plays a significant role in vehicle dynamics to improve the vehicle handling and achieve better stability performance. In order to study and evaluate the performance of the vehicles in addition to how to control it, it is necessary to identify obtain some models related to the dynamics of the vehicle as well as the tire models. This paper presents fundamentals of vehicle dynamics by introducing vehicle models and tire model, which have been widely adopted for vehicle motion control. This helps to get a basic idea of what parameters and states of a vehicle are important in vehicle motion control. This work is separated into four sections: vehicle planar model, full vehicle model, two degrees of freedom vehicle model (bicycle model) to design the controller, and wheel dynamic model.

The area of a Microgrid (μG) is a very fast-growing and promising system for overcoming power barriers. This paper examines the impacts of a microgrid system considering Electric Vehicle Grid Integration (EVGI) based on stochastic metaheuristic methods. One of the biggest challenges to slowing down global climate change is the transition to sustainable mobility. Renewable Energy Sources (RESs) integrated with Evs are considered a solution for the power and environmental issues needed to achieve Sustainable Development Goal Seven (SDG7) and Climate Action Goal 13 (CAG13). The aforementioned goals can be achieved by coupling Evs with the utility grid and other RESs using Vehicle-to-Grid (V2G) technology to form a hybrid system. Overloading is a challenge due to the unknown number of loads (unknown number of Evs). Thus, this study helps to establish the system impact of the uncertainties (arrival and departure Evs) by proposing Stochastic Monte Carlo Method (SMCM) to be addressed. The ...

The intricacy of the power system configuration, coupled with the contemporary trends in power generation and demand, renders the attainment of adequate supply quality a daunting task for distribution companies. Several regulations govern the power quality (PQ) of the electrical system. In addition, EN-50160 outlines the voltage characteristics supplied by public electricity networks, which directly impact distribution companies. Secondly, the EN-61000 standards series regulates the electromagnetic compatibility of networkconnected devices, which affects the loads. Both power companies and device manufacturers are responsible for ensuring and being impacted by the quality of supply. Artificial Intelligence (AI) techniques refer to a variety of methods and algorithms that enable machines to perform tasks that typically require humanlike intelligence, such as perception, reasoning, learning, and decision-making. AI techniques include machine learning, natural language processing, computer vision, robotics, expert systems, and other approaches that use algorithms to analyze and understand complex data, recognize patterns, and make predictions or decisions based on that data Notwithstanding the regulations, there are still unresolved aspects of the supply quality, one of the most significant being the location of the origin of disturbances. This article presents an investigation of the main techniques used to identify the cause of disturbances and locate their origin in the power grid,

To accommodate the intricate nature of increasing energy demands, the conventional grid (CG) has been augmented with advanced communication technologies such as advanced metering with sensors, demand response, energy storage systems, and the integration of electric vehicles. To ensure localized energy balance and reliability, Microgrids (MG) have been proposed. Microgrids are low or mediumvoltage distribution systems that operate with resilience, and regulate the exchange of power between the main grid, locally distributed generators (DGs), and consumers using intelligent energy management techniques. This paper provides a concise overview of MG, its operations, and a review of various energy management approaches. Within a MG control strategy, the energy management system (EMS) is the critical component responsible for balancing the available energy resources (CG, DG, ESS, and EVs) and loads, while contributing to the utility's profit. This article categorizes the methodologies utilized for EMS based on their structure, and control employed. Additionally, unexplored areas with potential for further research are identified.

Renewable energy capacity additions reached another record in 2021, as well as energy consumption. Despite logistical challenges, demand almost returned to pre-Covid levels, increased prices and challenges-moreover, the Russian Federation (from now on referred to as the Russian Federation). Energy and power sectors are reeling from "Russia's" invasion of Ukraine. An unprecedented energy crisis has arisen due to the collapse of the agriculture markets. As a result of energy prices rising, governments are trying to protect consumers, and efforts are being made to reduce dependence on Russian supplies and accelerate the process. Clean energy technologies are being transitioned to the use of renewable energy can reduce prices and dependence on fossil fuels. The longterm and short-term effects of fuels. The cost of installing solar PV and wind power is on the rise, despite the fact that prices of natural gas, oil, and electricity have risen in the last decade, reversing a decade-long trend of cost reductions. Due to the much faster rise in coal prices, the situation has improved more than before. Electricity generated from renewable sources is competitive. The question is, however, how quickly renewables can be implemented. Fossil fuel alternatives are subject to several uncertainties and will need to be dependent on several factors' impact.

The intricacy of the power system configuration, coupled with the contemporary trends in power generation and demand, renders the attainment of adequate supply quality a daunting task for distribution companies. Several regulations govern the power quality (PQ) of the electrical system. In addition, EN-50160 outlines the voltage characteristics supplied by public electricity networks, which directly impact distribution companies. Secondly, the EN-61000 standards series regulates the electromagnetic compatibility of network-connected devices, which affects the loads. Both power companies and device manufacturers are responsible for ensuring and being impacted by the quality of supply. Artificial Intelligence (AI) techniques refer to a variety of methods and algorithms that enable machines to perform tasks that typically require human-like intelligence, such as perception, reasoning, learning, and decision-making. AI techniques include machine learning, natural language processing, co...

This research presents a combination of artificial neural network (ANN) with the grey wolf optimizer (GWO) to improve the power quality of a grid-connected distributed power generation system (DPGS). To assess the effectiveness of the proposed algorithm, a grid-tied of small-scale wind energy conversion system (WECS) is chosen. The term power quality refers to voltage and frequency regulation, and limited harmonics. Power quality improvement is achieved through the cascaded control system's optimal tuning of three proportional-integral (PI) controllers of the grid-side inverter (GSI). However, because the DPGS model is computationally costly, the ANN model is utilized as an alternative model for DPGS. Furthermore, the ANN model is employed in conjunction with the GWO to boost the optimization precision and minimize the execution time of GWO. The considered power system was repetitively simulated to obtain the input-output datasets, which validate and train the ANN model. According to the ANN model's performance evaluation, the correlation coefficient (R) is close to one, while the mean squared error (MSE) is near zero. These findings demonstrate the ANN model's great accuracy in approximating the DPGS model. Using MATLAB/Simulink, the system's performance is evaluated using the optimum values obtained using GWO-ANN for various wind speed profiles. It showed the suggested power quality method's improved stability, convergence behavior, the effectiveness of the control mechanism, and the robustness of the proposed topology.